There's something I've been noticing lately... and the more I think about it, the harder it becomes to ignore.
When people talk about AI systems, the conversation often comes down to trust.
Can the system be trusted?
Are the answers reliable?
Should people depend on it?
And that makes sense.
Because trust is the part we experience directly.
It's what we feel when a system consistently gives us answers we believe in.
But the more I think about it, the more it feels like trust may not be where the story begins.
Before people trust a system...
something else has already happened.
We often think transparency creates trust.
But most trust is formed long before transparency is ever examined.
That's the part I keep coming back to.
People say they trust a system because it's transparent.
But in reality, many people trust systems they've never truly examined at all.
The trust comes first.
The transparency gets checked later.
Sometimes it never gets checked.
And that distinction feels more important than it first appears.
That's one reason I keep coming back to @OpenGradient when thinking about this.
Not because it asks for trust.
But because it keeps drawing attention toward the structure that allows trust to be questioned in the first place.
The more AI becomes part of everyday decisions, the harder it becomes to ignore that difference.
Because we spend a lot of time asking whether a system can be trusted.
But far less time asking what made that trust possible.
If trust is what we feel...
how often do we stop to examine what earned it in the first place?
#opg $OPG @OpenGradient
When people talk about AI systems, the conversation often comes down to trust.
Can the system be trusted?
Are the answers reliable?
Should people depend on it?
And that makes sense.
Because trust is the part we experience directly.
It's what we feel when a system consistently gives us answers we believe in.
But the more I think about it, the more it feels like trust may not be where the story begins.
Before people trust a system...
something else has already happened.
We often think transparency creates trust.
But most trust is formed long before transparency is ever examined.
That's the part I keep coming back to.
People say they trust a system because it's transparent.
But in reality, many people trust systems they've never truly examined at all.
The trust comes first.
The transparency gets checked later.
Sometimes it never gets checked.
And that distinction feels more important than it first appears.
That's one reason I keep coming back to @OpenGradient when thinking about this.
Not because it asks for trust.
But because it keeps drawing attention toward the structure that allows trust to be questioned in the first place.
The more AI becomes part of everyday decisions, the harder it becomes to ignore that difference.
Because we spend a lot of time asking whether a system can be trusted.
But far less time asking what made that trust possible.
If trust is what we feel...
how often do we stop to examine what earned it in the first place?
#opg $OPG @OpenGradient